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The ImageNet project is a large visual database designed for use in visual object recognition software research. More than 14 million [1] [2] images have been hand-annotated by the project to indicate what objects are pictured and in at least one million of the images, bounding boxes are also provided. [3]
ImageNet: Labeled object image database, used in the ImageNet Large Scale Visual Recognition Challenge: Labeled objects, bounding boxes, descriptive words, SIFT features 14,197,122 Images, text Object recognition, scene recognition 2009 (2014) [17] [18] [19] J. Deng et al. LSUN
However, it was not until 1963 the Topcon name became famous by introducing the Topcon RE Super, an event that took the entire camera industry by surprise: This camera featured through-the-lens exposure metering, at full lens aperture. The RE Super was fully prepared for professional work, supported by a choice of lenses and accessories to ...
TOPCON was established in September 1932 [4] based the merger of the surveying instruments division of K. Hattori & Co., Ltd. (now known as Seiko Holdinge Corporation) in order to manufacture the optical instruments for the Japanese Army.
ImageNets is an open source and platform independent (Windows & Linux) framework for rapid prototyping of machine vision algorithms. With the GUI ImageNet Designer, no programming knowledge is required to perform operations on images.
Fei-Fei Li (Chinese: 李飞飞; pinyin: Lǐ Fēifēi; born July 3, 1976) is a Chinese-American computer scientist known for establishing ImageNet, the dataset that enabled rapid advances in computer vision in the 2010s.
Hinton said its dataset was too small, so Malik recommended to him the ImageNet challenge. [18] While AlexNet and LeNet share essentially the same design and algorithm, AlexNet is much larger than LeNet and was trained on a much larger dataset on much faster hardware. Over the period of 20 years, both data and compute became cheaply available. [17]
Inception [1] is a family of convolutional neural network (CNN) for computer vision, introduced by researchers at Google in 2014 as GoogLeNet (later renamed Inception v1).). The series was historically important as an early CNN that separates the stem (data ingest), body (data processing), and head (prediction), an architectural design that persists in all modern